Functional Impact Score of Mitochondrial Variants and Its Relationship With Functional Connectivity of the Brain: Potential Origins of Premature Aging in Young Adulthood
Jazyk angličtina Země Spojené státy americké Médium print
Typ dokumentu časopisecké články
Grantová podpora
24-12183M
Grantová Agentura České Republiky
NU20J-04-00022
Agentura Pro Zdravotnický Výzkum České Republiky
LX22NPO5107
European Union - Next Generation EU
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy
LM2023069
Ministerstvo Školství, Mládeže a Tělovýchovy
857560
Horizon 2020 Framework Programme
Centre for Addiction and Mental Health Foundation
CEITEC 2020
Ministry of Education, Youth and Sports, Czech Republic
LQ1601
Ministry of Education, Youth and Sports, Czech Republic
PubMed
41479401
PubMed Central
PMC12757729
DOI
10.1002/hbm.70447
Knihovny.cz E-zdroje
- Klíčová slova
- dorsal attention network, functional impact score of mitochondrial variants (mtDNA FI score), general connectivity, language network, mitochondria dysfunction, young adulthood,
- MeSH
- dospělí MeSH
- epigeneze genetická MeSH
- konektom * MeSH
- lidé MeSH
- longitudinální studie MeSH
- magnetická rezonanční tomografie MeSH
- mitochondriální DNA * genetika MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mozek * diagnostické zobrazování fyziologie patofyziologie MeSH
- nervová síť * diagnostické zobrazování fyziologie MeSH
- předčasné stárnutí * genetika patofyziologie diagnostické zobrazování MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- mitochondriální DNA * MeSH
Alterations in mitochondrial DNA (mtDNA) have been associated with worse cognitive abilities in older adults and premature epigenetic aging in young adulthood. However, it is not clear how mitochondrial dysfunction affects brain function in young adulthood and whether cognition-related networks might be most affected. We tested whether mtDNA functional impact (FI) score might map onto specific patterns of between-network functional connectivity in young adults from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC). We also tested whether these relationships might be mediated by accelerated epigenetic aging, calculated using Horvath's epigenetic clock, CheekAge clock, and AltumAge clock. General connectivity method was used as a reliable marker of individual differences in brain function. We showed that a greater mtDNA FI score was associated with lower connectivity between the dorsal attention and language networks (beta = -0.41, p = 0.0007, AdjR2 = 0.15) and that there was suggestive evidence that this relationship might be mediated by accelerated epigenetic aging calculated using Horvath's epigenetic clock in young adulthood (ab = -0.061, SE = 0.04, 95% CI [-0.163; 0.001], 90% CI [-0.142; -0.002]). These findings were independent of sex, current BMI, and current substance use. Overall, we conclude that individuals with a greater mtDNA FI score might be at greater risk of experiencing worse attention to relevant linguistic inputs, greater difficulties with speech comprehension, and verbal working memory.
Department of Psychiatry University of Saskatchewan Saskatoon SK Canada
Department of Psychiatry University of Toronto Toronto ON Canada
Zobrazit více v PubMed
Arfanakis, K. , Cordes D., Haughton V. M., Moritz C. H., Quigley M. A., and Meyerand M. E.. 2000. “Combining Independent Component Analysis and Correlation Analysis to Probe Interregional Connectivity in fMRI Task Activation Datasets.” Magnetic Resonance Imaging 18, no. 8: 921–930. 10.1016/s0730-725x(00)00190-9. PubMed DOI
Bellizzi, D. , D'Aquila P., Giordano M., Montesanto A., and Passarino G.. 2012. “Global DNA Methylation Levels Are Modulated by Mitochondrial DNA Variants.” Epigenomics 4, no. 1: 17–27. 10.2217/epi.11.109. PubMed DOI
Craik, F. , and Salthouse T.. 2000. The Handbook of Aging and Cognition. Lawrence Erlbaum Associates Inc.
De Lima Camillo, L. P. , Lapierre L. R., and Singh R. A.. 2022. “A Pan‐Tissue DNA‐Methylation Epigenetic Clock Based on Deep Learning.” NPJ Aging 8: 4. 10.1038/s41514-022-00085-y. DOI
Deery, H. A. , Di Paolo R., Moran C., Egan G. F., and Jamadar S. D.. 2023. “Lower Brain Glucose Metabolism in Normal Ageing Is Predominantly Frontal and Temporal: A Systematic Review and Pooled Effect Size and Activation Likelihood Estimates Meta‐Analyses.” Human Brain Mapping 44, no. 3: 1251–1277. 10.1002/hbm.26119. PubMed DOI PMC
Deng, S. , Li J., Thomas Yeo B. T., and Gu S.. 2022. “Control Theory Illustrates the Energy Efficiency in the Dynamic Reconfiguration of Functional Connectivity.” Communications Biology 5, no. 1: 295. 10.1038/s42003-022-03196-0. PubMed DOI PMC
Dong, C. , Wei P., Jian X., et al. 2015. “Comparison and Integration of Deleteriousness Prediction Methods for Nonsynonymous SNVs in Whole Exome Sequencing Studies.” Human Molecular Genetics 24, no. 8: 2125–2137. 10.1093/hmg/ddu733. PubMed DOI PMC
Elliott, M. L. , Knodt A. R., Cooke M., et al. 2019. “General Functional Connectivity: Shared Features of Resting‐State and Task fMRI Drive Reliable and Heritable Individual Differences in Functional Brain Networks.” NeuroImage 189: 516–532. 10.1016/j.neuroimage.2019.01.068. PubMed DOI PMC
Fair, D. A. , Dosenbach N. U., Church J. A., et al. 2007. “Development of Distinct Control Networks Through Segregation and Integration.” Proceedings of the National Academy of Sciences of the United States of America 104, no. 33: 13507–13512. 10.1073/pnas.0705843104. PubMed DOI PMC
Fan, L. , and Yao Y. G.. 2011. “MitoTool: A Web Server for the Analysis and Retrieval of Human Mitochondrial DNA Sequence Variations.” Mitochondrion 11, no. 2: 351–356. 10.1016/j.mito.2010.09.013. PubMed DOI
Fedorenko, E. , Ivanova A. A., and Regev T. I.. 2024. “The Language Network as a Natural Kind Within the Broader Landscape of the Human Brain.” Nature Reviews. Neuroscience 25, no. 5: 289–312. 10.1038/s41583-024-00802-4. PubMed DOI
Fox, M. D. , Snyder A. Z., Zacks J. M., and Raichle M. E.. 2006. “Coherent Spontaneous Activity Accounts for Trial‐to‐Trial Variability in Human Evoked Brain Responses.” Nature Neuroscience 9, no. 1: 23–25. 10.1038/nn1616. PubMed DOI
Glasser, M. F. , Coalson T. S., Robinson E. C., et al. 2016. “A Multi‐Modal Parcellation of Human Cerebral Cortex.” Nature 536, no. 7615: 171–178. 10.1038/nature18933. PubMed DOI PMC
Gonçalves, V. F. , Giamberardino S. N., Crowley J. J., et al. 2018. “Examining the Role of Common and Rare Mitochondrial Variants in Schizophrenia.” PLoS One 13, no. 1: e0191153. 10.1371/journal.pone.0191153. PubMed DOI PMC
Goyal, M. S. , Vlassenko A. G., Blazey T. M., et al. 2017. “Loss of Brain Aerobic Glycolysis in Normal Human Aging.” Cell Metabolism 26, no. 2: 353–360.e353. 10.1016/j.cmet.2017.07.010. PubMed DOI PMC
Han, R. , Liang J., and Zhou B.. 2021. “Glucose Metabolic Dysfunction in Neurodegenerative Diseases‐New Mechanistic Insights and the Potential of Hypoxia as a Prospective Therapy Targeting Metabolic Reprogramming.” International Journal of Molecular Sciences 22, no. 11: 5887. 10.3390/ijms22115887. PubMed DOI PMC
Hayes, A. F. 2018. Introduction to Mediation, Moderation, and Conditional Process Analysis. Second Edition. A Regression‐Based Approach. Guilford Press.
Horvath, S. 2013. “DNA Methylation Age of Human Tissues and Cell Types.” Genome Biology 14, no. 10: R115. 10.1186/gb-2013-14-10-r115. PubMed DOI PMC
Howie, B. , Fuchsberger C., Stephens M., Marchini J., and Abecasis G. R.. 2012. “Fast and Accurate Genotype Imputation in Genome‐Wide Association Studies Through Pre‐Phasing.” Nature Genetics 44, no. 8: 955–959. 10.1038/ng.2354. PubMed DOI PMC
Inczedy‐Farkas, G. , Trampush J. W., Perczel Forintos D., et al. 2014. “Mitochondrial DNA Mutations and Cognition: A Case‐Series Report.” Archives of Clinical Neuropsychology 29, no. 4: 315–321. 10.1093/arclin/acu016. PubMed DOI
Ingman, M. , and Gyllensten U.. 2006. “ mtDB: Human Mitochondrial Genome Database, a Resource for Population Genetics and Medical Sciences.” Nucleic Acids Research 34, no. Database issue: D749–D751. 10.1093/nar/gkj010. PubMed DOI PMC
Ji, J. L. , Spronk M., Kulkarni K., Repovš G., Anticevic A., and Cole M. W.. 2019. “Mapping the Human Brain's Cortical–Subcortical Functional Network Organization.” NeuroImage 185: 35–57. 10.1016/j.neuroimage.2018.10.006. PubMed DOI PMC
Kato, T. , Kunugi H., Nanko S., and Kato N.. 2000. “Association of Bipolar Disorder With the 5178 Polymorphism in Mitochondrial DNA.” American Journal of Medical Genetics 96: 182–186. PubMed
Kato, T. , Kunugi H., Nanko S., and Kato N.. 2001. “Mitochondrial DNA Polymorphisms in Bipolar Disorder.” Journal of Affective Disorders 62: 151–164. PubMed
Keogh, M. J. , and Chinnery P. F.. 2015. “Mitochondrial DNA Mutations in Neurodegeneration.” Biochimica et Biophysica Acta 1847, no. 11: 1401–1411. 10.1016/j.bbabio.2015.05.015. PubMed DOI
Li, B. , Krishnan V. G., Mort M. E., et al. 2009. “Automated Inference of Molecular Mechanisms of Disease From Amino Acid Substitutions.” Bioinformatics 25, no. 21: 2744–2750. 10.1093/bioinformatics/btp528. PubMed DOI PMC
Lopes, F. C. A. 2020. “Mitochondrial Metabolism and DNA Methylation: A Review of the Interaction Between Two Genomes.” Clinical Epigenetics 12, no. 1: 182. 10.1186/s13148-020-00976-5. PubMed DOI PMC
López‐Otín, C. , Blasco M. A., Partridge L., Serrano M., and Kroemer G.. 2013. “The Hallmarks of Aging.” Cell 153, no. 6: 1194–1217. 10.1016/j.cell.2013.05.039. PubMed DOI PMC
Lunnon, K. , Keohane A., Pidsley R., et al. 2017. “Mitochondrial Genes Are Altered in Blood Early in Alzheimer's Disease.” Neurobiology of Aging 53: 36–47. 10.1016/j.neurobiolaging.2016.12.029. PubMed DOI
Manczak, M. , Park B. S., Jung Y., and Reddy P. H.. 2004. “Differential Expression of Oxidative Phosphorylation Genes in Patients With Alzheimer's Disease: Implications for Early Mitochondrial Dysfunction and Oxidative Damage.” Neuromolecular Medicine 5, no. 2: 147–162. 10.1385/nmm:5:2:147. PubMed DOI
Mareckova, K. , Marecek R., Andryskova L., Brazdil M., and Nikolova Y. S.. 2024. “Prenatal Exposure to Alcohol and Its Impact on Reward Processing and Substance Use in Adulthood.” Translational Psychiatry 14, no. 1: 220. 10.1038/s41398-024-02941-9. PubMed DOI PMC
Mareckova, K. , Mendes‐Silva A. P., Jáni M., et al. 2025. “Mitochondrial DNA Variants and Their Impact on Epigenetic and Biological Aging in Young Adulthood.” Translational Psychiatry 15, no. 1: 16. 10.1038/s41398-025-03235-4. PubMed DOI PMC
Mareckova, K. , Pacinkova A., Marecek R., et al. 2023. “Longitudinal Study of Epigenetic Aging and Its Relationship With Brain Aging and Cognitive Skills in Young Adulthood.” Frontiers in Aging Neuroscience 15: 1215957. 10.3389/fnagi.2023.1215957. PubMed DOI PMC
Mareckova, K. , Trbusek F., Marecek R., et al. 2025. “Maternal Depression During the Perinatal Period and Its Relationship With Emotion Regulation in Young Adulthood: An fMRI Study in a Prenatal Birth Cohort.” Psychological Medicine 55: e39. 10.1017/s0033291725000042. PubMed DOI PMC
Marečková, K. , Pačínková A., Klasnja A., et al. 2020. “Epigenetic Clock as a Correlate of Anxiety.” NeuroImage: Clinical 28: 102458. 10.1016/j.nicl.2020.102458. PubMed DOI PMC
McMahon, F. J. , Chen Y. S., Patel S., et al. 2000. “Mitochondrial DNA Sequence Diversity in Bipolar Affective Disorder.” American Journal of Psychiatry 157: 1058–1064. PubMed
Mendes‐Silva, A. P. , Nikolova Y. S., Rajji T. K., et al. 2024. “Exosome‐Associated Mitochondrial DNA in Late‐Life Depression: Implications for Cognitive Decline in Older Adults.” Journal of Affective Disorders 362: 217–224. PubMed PMC
Mosconi, L. , Pupi A., and De Leon M. J.. 2008. “Brain Glucose Hypometabolism and Oxidative Stress in Preclinical Alzheimer's Disease.” Annals of the New York Academy of Sciences 1147: 180–195. 10.1196/annals.1427.007. PubMed DOI PMC
Murphy, K. , Bodurka J., and Bandettini P. A.. 2007. “How Long to Scan? The Relationship Between fMRI Temporal Signal to Noise Ratio and Necessary Scan Duration.” NeuroImage 34, no. 2: 565–574. 10.1016/j.neuroimage.2006.09.032. PubMed DOI PMC
Nugent, S. , Castellano C. A., Goffaux P., et al. 2014. “Glucose Hypometabolism Is Highly Localized, but Lower Cortical Thickness and Brain Atrophy Are Widespread in Cognitively Normal Older Adults.” American Journal of Physiology. Endocrinology and Metabolism 306, no. 11: E1315–E1321. 10.1152/ajpendo.00067.2014. PubMed DOI
Pereira, L. , Soares P., Radivojac P., Li B., and Samuels D. C.. 2011. “Comparing Phylogeny and the Predicted Pathogenicity of Protein Variations Reveals Equal Purifying Selection Across the Global Human mtDNA Diversity.” American Journal of Human Genetics 88, no. 4: 433–439. 10.1016/j.ajhg.2011.03.006. PubMed DOI PMC
Picard, M. , and McEwen B. S.. 2014. “Mitochondria Impact Brain Function and Cognition.” Proceedings of the National Academy of Sciences of the United States of America 111, no. 1: 7–8. 10.1073/pnas.1321881111. PubMed DOI PMC
Piler, P. , Kandrnal V., Kukla L., et al. 2017. “Cohort Profile: The European Longitudinal Study of Pregnancy and Childhood (ELSPAC) in The Czech Republic.” International Journal of Epidemiology 46, no. 5: 1379. 10.1093/ije/dyw091. PubMed DOI PMC
Power, J. D. , Mitra A., Laumann T. O., Snyder A. Z., Schlaggar B. L., and Petersen S. E.. 2014. “Methods to Detect, Characterize, and Remove Motion Artifact in Resting State fMRI .” NeuroImage 84: 320–341. 10.1016/j.neuroimage.2013.08.048. PubMed DOI PMC
Prasun, P. 2020. “Role of Mitochondria in Pathogenesis of Type 2 Diabetes Mellitus.” Journal of Diabetes and Metabolic Disorders 19, no. 2: 2017–2022. 10.1007/s40200-020-00679-x. PubMed DOI PMC
Sanfey, A. , and Hastie R.. 2000. Cognitive Aging: A Primer. Psychology Press.
Scheffler, K. , Krohn M., Dunkelmann T., et al. 2012. “Mitochondrial DNA Polymorphisms Specifically Modify Cerebral β‐Amyloid Proteostasis.” Acta Neuropathologica 124, no. 2: 199–208. 10.1007/s00401-012-0980-x. PubMed DOI PMC
Shokhirev, M. N. , Torosin N. S., Kramer D. J., Johnson A. A., and Cuellar T. L.. 2024. “CheekAge: A Next‐Generation Buccal Epigenetic Aging Clock Associated With Lifestyle and Health.” Geroscience 46, no. 3: 3429–3443. 10.1007/s11357-024-01094-3. PubMed DOI PMC
Smith, S. M. , Fox P. T., Miller K. L., et al. 2009. “Correspondence of the Brain's Functional Architecture During Activation and Rest.” Proceedings of the National Academy of Sciences of the United States of America 106, no. 31: 13,040–13,045. 10.1073/pnas.0905267106. PubMed DOI PMC
Soini, H. K. , Moilanen J. S., Vilmi‐Kerälä T., Finnilä S., and Majamaa K.. 2013. “Mitochondrial DNA Variant m.15218A > G in Finnish Epilepsy Patients Who Have Maternal Relatives With Epilepsy, Sensorineural Hearing Impairment or Diabetes Mellitus.” BMC Medical Genetics 14: 73. 10.1186/1471-2350-14-73. PubMed DOI PMC
Subtirelu, R. C. , Teichner E. M., Su Y., et al. 2023. “Aging and Cerebral Glucose Metabolism: (18)F‐FDG‐PET/CT Reveals Distinct Global and Regional Metabolic Changes in Healthy Patients.” Life 13, no. 10: 2044. 10.3390/life13102044. PubMed DOI PMC
Tachi, R. , Ohi K., Nishizawa D., et al. 2023. “Mitochondrial Genetic Variants Associated With Bipolar Disorder and Schizophrenia in a Japanese Population.” International Journal of Bipolar Disorders 11: 26. PubMed PMC
Takagi, K. 2025. “A Reduction in Energy Costs Induces Integrated States of Brain Dynamics.” Scientific Reports 15, no. 1: 11421. 10.1038/s41598-025-96120-5. PubMed DOI PMC
Teschendorff, A. E. , Marabita F., Lechner M., et al. 2013. “A Beta‐Mixture Quantile Normalization Method for Correcting Probe Design Bias in Illumina Infinium 450 k DNA Methylation Data.” Bioinformatics 29, no. 2: 189–196. 10.1093/bioinformatics/bts680. PubMed DOI PMC
Tian, Y. , Morris T. J., Webster A. P., et al. 2017. “ChAMP: Updated Methylation Analysis Pipeline for Illumina BeadChips.” Bioinformatics 33, no. 24: 3982–3984. 10.1093/bioinformatics/btx513. PubMed DOI PMC
Tomasi, D. , and Volkow N. D.. 2012. “Aging and Functional Brain Networks.” Molecular Psychiatry 17, no. 5: 471–549–558. 10.1038/mp.2011.81. PubMed DOI PMC
Tomasi, D. , Wang G. J., and Volkow N. D.. 2013. “Energetic Cost of Brain Functional Connectivity.” Proceedings of the National Academy of Sciences of the United States of America 110, no. 33: 13642–13647. 10.1073/pnas.1303346110. PubMed DOI PMC
Vos, M. 2022. “Mitochondrial Complex I Deficiency: Guilty in Parkinson's Disease.” Signal Transduction and Targeted Therapy 7, no. 1: 136. 10.1038/s41392-022-00983-3. PubMed DOI PMC
Vossel, S. , Geng J. J., and Fink G. R.. 2014. “Dorsal and Ventral Attention Systems: Distinct Neural Circuits but Collaborative Roles.” Neuroscientist 20, no. 2: 150–159. 10.1177/1073858413494269. PubMed DOI PMC
Yeo, B. T. , Krienen F. M., Sepulcre J., et al. 2011. “The Organization of the Human Cerebral Cortex Estimated by Intrinsic Functional Connectivity.” Journal of Neurophysiology 106, no. 3: 1125–1165. 10.1152/jn.00338.2011. PubMed DOI PMC
Zhang, H. , Gertel V. H., Cosgrove A. L., and Diaz M. T.. 2021. “Age‐Related Differences in Resting‐State and Task‐Based Network Characteristics and Cognition: A Lifespan Sample.” Neurobiology of Aging 101: 262–272. 10.1016/j.neurobiolaging.2020.10.025. PubMed DOI PMC